code: def test_train_and_eval(self, secondary_loss):
      data_dir = tf.compat.v1.test.get_temp_dir()
      data_file = os.path.join(data_dir, "libvsvm.txt")
      if tf.io.gfile.exists(data_file):
          tf.io.gfile.remove(data_file)
  
      with open(data_file, "wt") as writer:
          writer.write(LIBSVM_DATA)
  
      output_dir = os.path.join(data_dir, secondary_loss or "")
  
      with flagsaver.flagsaver(
          train_path=data_file,
          vali_path=data_file,
          test_path=data_file,
          output_dir=output_dir,
          loss="pairwise_logistic_loss",
          secondary_loss=secondary_loss,
          num_train_steps=10,
          list_size=10,
          group_size=2,
          num_features=100,
      ):
          tf_ranking_libsvm.train_and_eval()
  
      if tf.io.gfile.exists(output_dir):
          tf.io.gfile.rmtree(output_dir)
  
file_path: ranking/tensorflow_ranking/examples/tf_ranking_libsvm_test.py
imports: import os
  from absl import flags
  from absl.testing import flagsaver
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_ranking.examples import tf_ranking_libsvm
label_desc: Use image node_id 1 for calling the TfRankingLibSVMTest obj's underlying member method code with example usage: obj.test_train_and_eval(secondary_loss) without return types